Domain Concept-Based Queries for Cancer Research Data Sources

被引:0
|
作者
Beltran, Alejandra Gonzalez [1 ]
Finkelstein, Anthony [1 ]
Wilkinson, J. Max [2 ]
Kramer, Jeff [3 ]
机构
[1] UCL, Dept Comp Sci, London, England
[2] NCRI Informat Initiat, London, England
[3] Imperial Coll London, Dept Comp Sci, London, England
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Biomedical scientists generate, access, validate and interpret multiple distributed and heterogeneous data sets. Semantic annotations for these data sets are paramount for exchanging and using the data, and take the form of concepts from a domain ontology. ONIX is a platform that facilitates the access to cancer research data resources and one of its goals is to interoperate with caGrid - a grid computing infrastructure for data sharing. In this paper, we present the ONIX approach to building a semantic layer with support for concept-based queries, which exploit semantic annotations of resources, focusing on caGrid resources. The main contributions of this work are: the automatic generation of OWL ontologies from resources' metadata; concept-based query construction and validation; rewriting and translation from concept-based queries to the caGrid query, language.
引用
收藏
页码:318 / +
页数:2
相关论文
共 50 条
  • [1] Personalized concept-based clustering of search engine queries
    Leung, Kenneth Wai-Ting
    Ng, Wilfred
    Lee, Dik Lun
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2008, 20 (11) : 1505 - 1518
  • [2] Learning to rank images for complex queries in concept-based search
    Cui, Chaoran
    Shen, Jialie
    Chen, Zhumin
    Wang, Shuaiqiang
    Ma, Jun
    NEUROCOMPUTING, 2018, 274 : 19 - 28
  • [3] Enriching the Semantics of Queries with Bayesian Belief Network in Concept-based Search
    Lee, Jae-won
    Kim, Han-joon
    Chang, Juno
    Lee, Sang-goo
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2010, 13 (04): : 1315 - 1331
  • [4] Concept-Based Approach for Research Paper Recommendation
    Sharma, Ritu
    Gopalani, Dinesh
    Meena, Yogesh
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2017, 2017, 10597 : 687 - 692
  • [5] On concept-based definition of domain-specific languages
    Liu, Y
    Zhang, NX
    FORMAL METHODS AND SOFTWARE ENGINEERING, PROCEEDINGS, 2002, 2495 : 237 - 248
  • [6] Concept-based ranking: a case study in the juridical domain
    Silveira, ML
    Ribeiro-Neto, B
    INFORMATION PROCESSING & MANAGEMENT, 2004, 40 (05) : 791 - 805
  • [7] An intelligent approach to handling imperfect information in concept-based natural language queries
    Owei, V
    ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2002, 20 (03) : 291 - 328
  • [8] Predicting Concept-Based Research Trends with Rhetorical Framing
    Yu, Jifan
    Pan, Liangming
    Li, Juanzi
    Du, Xiaoping
    KNOWLEDGE GRAPH AND SEMANTIC COMPUTING: KNOWLEDGE COMPUTING AND LANGUAGE UNDERSTANDING (CCKS 2018), 2019, 957 : 116 - 128
  • [9] Concept-Based Visual Analysis of Dynamic Textual Data
    Xiang S.
    Ouyang F.
    Liu S.
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2020, 32 (04): : 531 - 541
  • [10] Personalized concept-based search on the Linked Open Data
    Sah, Melike
    Wade, Vincent
    JOURNAL OF WEB SEMANTICS, 2016, 36 : 32 - 57